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基于配额指标重要性视角的中国碳排放配额再分配 被引量:8

Research on the redistribution of carbon emission quotas in China based on the importance of indicators to carbon emissions
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摘要 提出用与碳排放“同步变化程度”来衡量配额指标重要性的思想,对中国各省份碳排放配额进行再分配.首先在公平和效率原则基础上选取碳排放的影响因素作为分配指标,其次采用灰色关联分析法分别测算出各地区各指标与碳排放量的同步变动程度,以得到各地区各指标在配额分配中的比重.最后测算出我国29个省区2020~2030年的碳排放配额与排放空间.结果表明,人口基数及经济发展指标对各地碳排放有较强的同步变动关联性,因此应该被赋予更高的权重;配额最多的地区包括广东、北京、江苏、山东、上海,最少的地区则包括宁夏、贵州、青海、吉林、新疆.盈余分析发现,北京地区的碳排放空间有较多盈余;浙江等5个省区已达较饱和状态;山东等4个省区则处于较严重的溢出状态,在未来10年内需承担较重的减排压力. This paper puts forward the idea of using the"synchronous trend of change"in carbon emissions to measure the importance of quota indicators that distributes carbon emission quotas in various provinces of China.Firstly,based on the principles of fairness and efficiency,the influence factors of carbon emissions are selected as allocation indicators.Secondly,the grey correlation method is adopted to calculate the"synchronous trend"of each indicator and carbon emissions in each region,so as to obtain the weight of each indicator in quota allocation.Finally,the carbon emission quota and emission space of 29provinces from 2020 to 2030 are calculated.The results show that indicators such as population and economic are strongly correlated with local carbon emissions.Therefore,they should be attached more importance to.Guangdong,Beijing,Jiangsu,Shandong and Shanghai have the largest quotas,while Ningxia,Guizhou,Qinghai,Jilin and Xinjiang have the fewest ones.According to our analysis,Beijing has surplus carbon emission space;the space for Zhejiang and other four provinces is quite saturated.;and the situation faced by Shandong and other three provinces and regions is more severe because of spillover,where the pressure to reduce emissions will be extremely heavy in the next decade.
作者 周迪 王文捷 陈梓佳 ZHOU Di;WANG Wen-jie;CHEN Zi-jia(School of Mathematics and Statistics,Guangdong University of Foreign Studies,Guangzhou 510006,China)
出处 《中国环境科学》 EI CAS CSCD 北大核心 2020年第12期5551-5560,共10页 China Environmental Science
基金 教育部人文社会科学研究项目(20YJC790191) 广东省自然科学基金资助项目(2018A030310044)。
关键词 灰色关联分析法 碳排放配额分配 公平和效率原则 grey correlation analysis allocation of carbon emission quota equity and efficiency principles
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